Spatial difference measurement

ABSTRACT

A spatial difference measurement method, can include generating first key features of a first skeleton of a nominal 3D model of an object and extrapolating the first key features onto the nominal 3D model. The method can include creating an actual 3D model of the object during or after a construction process (real or simulated). The method can include generating second key features of a second skeleton of the actual 3D model of the object and extrapolating the second key features onto the actual 3D model of the object. The method can include comparing the first key features extrapolated on the nominal 3D model to the second key features extrapolated on the actual 3D model to determine one or more distances between the first and second key features to measure a spatial difference between the nominal 3D model and the object during or after construction.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 U.S.C. § 119(a) to ChinesePatent Application No. CN201910681586.5 filed in China on Jul. 26, 2019,the entire contents of which are herein incorporated by reference.

FIELD

This disclosure relates to spatial difference measurement, e.g., foradditive manufacturing systems and processes for the purpose ofdistortion compensation.

BACKGROUND

Change of geometry occurs during Additive Manufacturing (AM) process dueto volume shrinkage, springback due to stress relief, etc. One of themajor steps in certain additive manufacturing processes is to measurethe spatial difference between pairwise 3D models, e.g., an inputnominal model and an actual additively manufactured (simulated or real)model (e.g., for distortion compensation, experimental/printing resultsevaluation). Traditional methods need to manually choose referencepoints/surface/edge, compare a distance between surface points on thesetwo models, and report their accuracy in terms of length, angular, edge,etc. However, these kinds of methods heavily rely on the choice ofreference, such that slight change will cause significant difference inmeasurement results. Thus, traditional methods can be unreliable andinaccurate.

Such conventional methods and systems have generally been consideredsatisfactory for their intended purpose. However, there is still a needin the art for improved spatial difference measurement methods andsystems. The present disclosure provides a solution for this need.

SUMMARY

A spatial difference measurement method can include generating first keyfeatures of a first skeleton of a nominal 3D model of an object andextrapolating the first key features onto the nominal 3D model. Themethod can include creating an actual 3D model of the object during orafter a construction process (real or simulated). The method can includegenerating second key features of a second skeleton of the actual 3Dmodel of the object and extrapolating the second key features onto theactual 3D model of the object. The method can include comparing thefirst key features extrapolated on the nominal 3D model to the secondkey features extrapolated on the actual 3D model to determine one ormore distances between the first and second key features to measure aspatial difference between the nominal 3D model and the object during orafter construction.

In certain embodiments, the method can include receiving the nominal 3Dmodel of an object, and generating the first skeleton based on thenominal 3D model. The method can include generating the second skeletonbased on the actual 3D model.

Generating the first skeleton can include converting the nominal 3Dmodel into a first finite element mesh using median axis method, forexample. In certain embodiments, generating the second skeleton caninclude converting the actual 3D model into a second finite element meshusing median axis method.

In certain embodiments, generating the first key features and generatingthe second key features can include using nodes of the first skeletonand the second skeleton, respectively. Extrapolating the first keyfeatures and extrapolating the second key features can includeprojecting the first key features and second key features to a surfaceof the nominal 3D model and the actual 3D model, respectively, forexample.

In certain embodiments, the construction process can be an additivemanufacturing process and the method can include additivelymanufacturing the object based on nominal 3D model. Comparing can bedone in real time and the method can include modifying one or morecharacteristics of the additive manufacturing process to account for themeasured spatial difference.

In accordance with at least one aspect of this disclosure, anon-transitory computer readable medium can include computer executableinstructions configured to cause a computer to perform any suitablemethod(s) and/or portion(s) thereof disclosed herein (e.g., describedabove). Any other suitable method(s) and/or portion(s) thereof arecontemplated herein.

In accordance with at least one aspect of this disclosure, a system caninclude a spatial difference measurement module configured to performany suitable method(s) and/or portion(s) thereof disclosed herein (e.g.,described above). The spatial difference measurement module can beconfigured to output a spatial difference value, for example. Thespatial difference measurement module can be configured to control anadditive manufacturing process and to modify at least one characteristicof the additive manufacturing process as a function of the spatialdifference value. The module can include any suitable hardware and/orsoftware to perform the desired function as appreciated by those havingordinary skill in the art in view of this disclosure.

These and other features of the embodiments of the subject disclosurewill become more readily apparent to those skilled in the art from thefollowing detailed description taken in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

So that those skilled in the art to which the subject disclosureappertains will readily understand how to make and use the devices andmethods of the subject disclosure without undue experimentation,embodiments thereof will be described in detail herein below withreference to certain figures, wherein:

FIG. 1 is a flow diagram of an embodiment of a method in accordance withthis disclosure;

FIG. 2 is a perspective view of an embodiment of a digital nominal 3Dmodel of an object in accordance with this disclosure;

FIG. 3 is a plan view of a first skeleton model of the nominal 3D modelof FIG. 1 and generation of first key features on the first skeleton;

FIG. 4 is a plan view of the nominal 3D model of FIG. 1, showing thefirst key features of FIG. 2 extrapolated to the nominal 3D model (e.g.,projected to the outer surface); and

FIG. 5 shows the comparison of the nominal 3D model to an actual 3Dmodel to measure spatial difference based on relative locations of thefirst key features of the nominal 3D model relative to second keyfeatures of the actual 3D model.

DETAILED DESCRIPTION

Reference will now be made to the drawings wherein like referencenumerals identify similar structural features or aspects of the subjectdisclosure. For purposes of explanation and illustration, and notlimitation, an illustrative view of an embodiment of a method inaccordance with the disclosure is shown in FIG. 1 and is designatedgenerally by reference character 100. Other embodiments and/or aspectsof this disclosure are shown in FIGS. 2-5.

Referring to FIGS. 1, 2, and 3, a spatial difference measurement methodcan include generating (e.g., at block 101) first key features 201 of afirst skeleton 300 of a nominal 3D model 200 of an object (e.g., anysuitable article of manufacture). Referring additionally to FIG. 4, themethod 100 can include extrapolating (e.g., at block 103) the first keyfeatures 301 onto the nominal 3D model 200. As disclosed herein, a 3Dmodel can be a CAD model or any other suitable computer generated model.

Referring additionally to FIG. 5, the method 100 can include creating(e.g., at block 105) an actual 3D model 500 of the object during orafter a construction process (real or simulated). For example, digitalimage correlation (DIC) can be used during a build process or after abuild process to form the actual 3D model 500 based on digital images.

The method 100 can include generating (e.g., at block 107) second keyfeatures 601 of a second skeleton 600 of the actual 3D model of theobject and extrapolating (e.g., at block 109) the second key features601 onto the actual 3D model 500 of the object, e.g., as shown in FIG.5. The method 100 can include comparing (e.g., at block 111) the firstkey features 301 extrapolated on the nominal 3D model 200 to the secondkey features 601 extrapolated on the actual 3D model 500 to determineone or more distances between the first and second key features 301, 601to measure a spatial difference between the nominal 3D model 200 and theobject during or after construction (e.g., represented by the actual 3Dmodel 500 which can be deformed from the nominal 3D model 200). It iscontemplated that the construction of the object can be real orsimulated to create the actual 3D model 500.

In certain embodiments, the method 100 can include receiving the nominal3D model 200 of an object, and generating the first skeleton 300 basedon the nominal 3D model 200. However, it is contemplated that the firstskeleton 300 can be provided instead of generated as part of the method100.

In certain embodiments, the method 100 can include generating the secondskeleton 600 based on the actual 3D model 500. This can be done inreal-time (e.g., using DIC) or after the completion of the construction(real or simulated) of the object.

Generating the first skeleton 300 can include converting the nominal 3Dmodel 200 into a first finite element mesh, e.g., as shown, using medianaxis method, for example. In certain embodiments, generating the secondskeleton 600 can include converting the actual 3D model 500 into asecond finite element mesh using median axis method. Any other suitablemethod to create the first and/or second skeleton 300, 600 iscontemplated herein.

In certain embodiments, generating the first key features 301 andgenerating the second key features 601 can include using nodes of thefirst skeleton 300 and the second skeleton 600, respectively. Forexample, the nodes can be connection points of at least some, if notall, of the finite elements (e.g., the stick like members shown) of therespective skeleton 300, 600. Any other suitable points for key features301, 601 are contemplated herein.

As shown in FIGS. 4 and 5, extrapolating the first key features 301 andextrapolating the second key features 601 can include projecting thefirst key features 301 and second key features 601 to a surface 203, 503of the nominal 3D model 200 and the actual 3D model 500, respectively,for example. In certain embodiments, the one or more key features 601next to a single corner can be projected to the single corner (e.g., asshown in FIGS. 4 and 5).

In certain embodiments, the construction process (real or simulated) canbe an additive manufacturing process (e.g., laser powder bed fusion,plastic deposition, etc.) and the method 100 can include additivelymanufacturing the object based on nominal 3D model 200. In this regard,the nominal 3D model 200 can be sliced into layers for layer-wisemanufacture, e.g., as appreciated by those having ordinary skill in theart. Comparing 111 can be done in real time (e.g., by a machinecontroller of an additive manufacturing machine), e.g., with each layer,to monitor the construction process in real time (e.g., to predict anultimate outcome of a finally constructed object). In this regard, it iscontemplated that the method 100 can be performed layer by layer suchthat each layer of the actual 3D model is modeled and compared to therespective layer of the nominal 3D model 200 as the construction processproceeds. In certain embodiments, a predicted final model can be createdbased on less than all layers and/or compared to the nominal 3D model200, for example.

Using one or more embodiments above, the method 100 can includemodifying one or more characteristics (e.g., by the machine controller)of the additive manufacturing process to account for the measuredspatial difference. For example, if a spatial difference between layersof each model (or between a predicted final model and the nominal model)is above a threshold, a laser power and/or scan speed can be modifiedfor at least the next layer to modify thermal gradients to causeregression to the nominal model (to reduce spatial difference). Anysuitable process steps can be taken to cause regression to the nominalmodel, for example.

Certain embodiments of a skeleton setup method can include median axismethod (e.g., see Tam, Roger, and Wolfgang Heidrich. “Shapesimplification based on the medial axis transform.” Visualization, 2003.VIS 2003. IEEE. IEEE, 2003, incorporated by reference herein) to set upa skeleton for a 3D model. FIG. 2 shows an example of skeleton detectionresults of a 7-support bridge model. The result is composed ofcollections of joints and parts, as shown in FIG. 3. In the exampleshown, the 7-support bridge results in 13 parts and 14 joints.

Certain embodiments of a key feature generation method can includeutilizing the joint points to identify key features for spatialdifference measurement. Usually measurement of a 3D part is conducted onsurface, therefore the joint points can be projected back onto thesurface of the 3D model and the key features will then be extrapolatedonto the 3D model for use in comparison, as shown in FIGS. 4 and 5.

In accordance with at least one aspect of this disclosure, anon-transitory computer readable medium can include computer executableinstructions configured to cause a computer to perform any suitablemethod(s) and/or portion(s) thereof disclosed herein (e.g., describedabove). Any other suitable method(s) and/or portion(s) thereof arecontemplated herein. For example, a machine controller of an additivemanufacturing machine can include a non-transitory computer readablemedium and be configured to execute any suitable portion(s) of anysuitable method disclosed herein, e.g., as described above). Forexample, the machine controller can perform all portions of one or moremethods disclosed herein, e.g., as described above.

In accordance with at least one aspect of this disclosure, a system caninclude a spatial difference measurement module configured to performany suitable method(s) and/or portion(s) thereof disclosed herein (e.g.,described above). The spatial difference measurement module can beconfigured to output a spatial difference value, for example. Thespatial difference measurement module can be configured to control anadditive manufacturing process and to modify at least one characteristicof the additive manufacturing process as a function of the spatialdifference value. The spatial difference measurement module can includeany suitable hardware and/or software to perform the desired function asappreciated by those having ordinary skill in the art in view of thisdisclosure.

Embodiments include a spatial difference measurement method to evaluateshape change of an object relative to its intended shape bothefficiently and effectively. Embodiments take advantage of a skeleton ofa 3D model, the topology and geometry of a class of 3D objects, toconduct shape alignment as well as define spatial residual. Usingembodiments of this disclosure, spatial difference is structure-based,which means the measurement results are view point and affine invariant.Previous methods usually need to extract and scan surface points bysoftware to i) build mesh, ii) select reference, and iii) calculate “L2”distance among them. Instead, certain embodiments only compute thespatial difference between the nominal and detected key features.

Certain embodiments can include a skeleton-based 3D model differencemeasurement method including i) skeleton setup to capture the 3Dstructure of pairwise given 3D models (e.g., a nominal model and anactual/deformed model), ii) key feature detection, e.g., to alignskeleton with the 3D model (i.e., vertex of mesh/finite element nodes),iii) use of a real time tool such as DIC to track the final shape inexperiment, and iv) determine spatial difference as:

ε=∥X−X′∥2

where X and X′ are aligned key features of nominal and actual (e.g.,deformed) models, respectively.

Using embodiments disclosed herein, the spatial differences can becaptured from a 3D model skeleton, which reflects the 3D shape profilewhich is both scale and affine invariant. The key features can be asubset of node points of a 3D model, and thus, many outliers introducedby scanning and shape changes during simulation can be avoided. Certainembodiments can be used in real time, e.g., during printing experiments,using tools like DIC that can track the strain. Embodiments can be usedfor potential distortion compensation in additive manufacturing duringthe building of the part, for example.

As will be appreciated by those skilled in the art, aspects of thepresent disclosure may be embodied as a system, method or computerprogram product. Accordingly, aspects of this disclosure may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.), or anembodiment combining software and hardware aspects, all possibilities ofwhich can be referred to herein as a “circuit,” “module,” or “system.” A“circuit,” “module,” or “system” can include one or more portions of oneor more separate physical hardware and/or software components that cantogether perform the disclosed function of the “circuit,” “module,” or“system”, or a “circuit,” “module,” or “system” can be a singleself-contained unit (e.g., of hardware and/or software). Furthermore,aspects of this disclosure may take the form of a computer programproduct embodied in one or more computer readable medium(s) havingcomputer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thisdisclosure may be written in any combination of one or more programminglanguages, including an object oriented programming language such asJava, Smalltalk, C++ or the like and conventional procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The program code may execute entirely on the user's computer,partly on the user's computer, as a stand-alone software package, partlyon the user's computer and partly on a remote computer or entirely onthe remote computer or server. In the latter scenario, the remotecomputer may be connected to the user's computer through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider).

Aspects of the this disclosure may be described above with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of thisdisclosure. It will be understood that each block of any flowchartillustrations and/or block diagrams, and combinations of blocks in anyflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inany flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified herein.

Those having ordinary skill in the art understand that any numericalvalues disclosed herein can be exact values or can be values within arange. Further, any terms of approximation (e.g., “about”,“approximately”, “around”) used in this disclosure can mean the statedvalue within a range. For example, in certain embodiments, the range canbe within (plus or minus) 20%, or within 10%, or within 5%, or within2%, or within any other suitable percentage or number as appreciated bythose having ordinary skill in the art (e.g., for known tolerance limitsor error ranges).

The articles “a”, “an”, and “the” as used herein and in the appendedclaims are used herein to refer to one or to more than one (i.e., to atleast one) of the grammatical object of the article unless the contextclearly indicates otherwise. By way of example, “an element” means oneelement or more than one element.

The phrase “and/or,” as used herein in the specification and in theclaims, should be understood to mean “either or both” of the elements soconjoined, i.e., elements that are conjunctively present in some casesand disjunctively present in other cases. Multiple elements listed with“and/or” should be construed in the same fashion, i.e., “one or more” ofthe elements so conjoined. Other elements may optionally be presentother than the elements specifically identified by the “and/or” clause,whether related or unrelated to those elements specifically identified.Thus, as a non-limiting example, a reference to “A and/or B”, when usedin conjunction with open-ended language such as “comprising” can refer,in one embodiment, to A only (optionally including elements other thanB); in another embodiment, to B only (optionally including elementsother than A); in yet another embodiment, to both A and B (optionallyincluding other elements); etc.

As used herein in the specification and in the claims, “or” should beunderstood to have the same meaning as “and/or” as defined above. Forexample, when separating items in a list, “or” or “and/or” shall beinterpreted as being inclusive, i.e., the inclusion of at least one, butalso including more than one, of a number or list of elements, and,optionally, additional unlisted items. Only terms clearly indicated tothe contrary, such as “only one of” or “exactly one of,” or, when usedin the claims, “consisting of,” will refer to the inclusion of exactlyone element of a number or list of elements. In general, the term “or”as used herein shall only be interpreted as indicating exclusivealternatives (i.e., “one or the other but not both”) when preceded byterms of exclusivity, such as “either,” “one of,” “only one of,” or“exactly one of.”

Any suitable combination(s) of any disclosed embodiments and/or anysuitable portion(s) thereof are contemplated herein as appreciated bythose having ordinary skill in the art.

The embodiments of the present disclosure, as described above and shownin the drawings, provide for improvement in the art to which theypertain. While the subject disclosure includes reference to certainembodiments, those skilled in the art will readily appreciate thatchanges and/or modifications may be made thereto without departing fromthe spirit and scope of the subject disclosure.

What is claimed is:
 1. A spatial difference measurement method,comprising: generating first key features of a first skeleton of anominal 3D model of an object; extrapolating the first key features ontothe nominal 3D model; creating an actual 3D model of the object duringor after a construction process; generating second key features of asecond skeleton of the actual 3D model of the object; extrapolating thesecond key features onto the actual 3D model of the object; andcomparing the first key features extrapolated on the nominal 3D model tothe second key features extrapolated on the actual 3D model to determineone or more distances between the first and second key features tomeasure a spatial difference between the nominal 3D model and the objectduring or after construction.
 2. The method of claim 1, furthercomprising receiving the nominal 3D model of an object, and generatingthe first skeleton based on the nominal 3D model.
 3. The method of claim2, wherein the method includes generating the second skeleton based onthe actual 3D model.
 4. The method of claim 3, wherein generating thefirst skeleton includes converting the nominal 3D model into a firstfinite element mesh using median axis method.
 5. The method of claim 4,wherein generating the second skeleton includes converting the actual 3Dmodel into a second finite element mesh using median axis method.
 6. Themethod of claim 1, wherein generating the first key features andgenerating the second key features includes using nodes of the firstskeleton and the second skeleton, respectively.
 7. The method of claim6, wherein extrapolating the first key features and extrapolating thesecond key features includes projecting the first key features andsecond key features to a surface of the nominal 3D model and the actual3D model, respectively.
 8. The method of claim 7, wherein theconstruction process is an additive manufacturing process and the methodincludes additively manufacturing the object based on nominal 3D model.9. The method of claim 8, wherein comparing is done in real time and themethod includes modifying one or more characteristics of the additivemanufacturing process to account for the measured spatial difference.10. A non-transitory computer readable medium comprising computerexecutable instructions configured to cause a computer to perform amethod, the method comprising: generating first key features of a firstskeleton of a nominal 3D model of an object; extrapolating the first keyfeatures onto the nominal 3D model; creating an actual 3D model of theobject during or after a construction process; generating second keyfeatures of a second skeleton of the actual 3D model of the object;extrapolating the second key features onto the actual 3D model of theobject; and comparing the first key features extrapolated on the nominal3D model to the second key features extrapolated on the actual 3D modelto determine one or more distances between the first and second keyfeatures to measure a spatial difference between the nominal 3D modeland the object during or after construction.
 11. The non-transitorycomputer readable medium of claim 10, wherein the method includesreceiving the nominal 3D model of an object, and generating the firstskeleton based on the nominal 3D model.
 12. The non-transitory computerreadable medium of claim 11, wherein the method includes generating thesecond skeleton based on the actual 3D model.
 13. The non-transitorycomputer readable medium of claim 12, wherein generating the firstskeleton includes converting the nominal 3D model into a first finiteelement mesh using median axis method.
 14. The non-transitory computerreadable medium of claim 13, wherein generating the second skeletonincludes converting the actual 3D model into a second finite elementmesh using median axis method.
 15. The non-transitory computer readablemedium of claim 10, wherein generating the first key features andgenerating the second key features includes using nodes of the firstskeleton and the second skeleton, respectively.
 16. The non-transitorycomputer readable medium of claim 15, wherein extrapolating the firstkey features and extrapolating the second key features includesprojecting the first key features and second key features to a surfaceof the nominal 3D model and the actual 3D model, respectively.
 17. Thenon-transitory computer readable medium of claim 16, wherein theconstruction process is an additive manufacturing process and the methodincludes additively manufacturing the object based on nominal 3D model.18. The non-transitory computer readable medium of claim 17, whereincomparing is done in real time and the method includes modifying one ormore characteristics of the additive manufacturing process to accountfor the measured spatial difference.
 19. A system, comprising: a spatialdifference measurement module configured to: generate first key featuresof a first skeleton of a nominal 3D model of an object; extrapolate thefirst key features onto the nominal 3D model; create an actual 3D modelof the object during or after a construction process; generate secondkey features of a second skeleton of the actual 3D model of the object;extrapolate the second key features onto the actual 3D model of theobject; compare the first key features extrapolated on the nominal 3Dmodel to the second key features extrapolated on the actual 3D model todetermine one or more distances between the first and second keyfeatures to measure a spatial difference between the nominal 3D modeland the object during or after construction; and output a spatialdifference value.
 20. The apparatus of claim 19, wherein the spatialdifference measurement module is configured control an additivemanufacturing process, wherein the special difference measurement moduleis configured to modify at least one characteristic of the additivemanufacturing process as a function of the spatial difference value.